Effects of tissue decalcification on the quantification of breast cancer biomarkers by digital image analysis

Diagnostic Pathology

Beatrice S Knudsen⁶  Bonnie Balzer⁵  James Mirocha²  Kolja Wawrowsky⁶  Sambit Mohanty³  Shawn Maclary⁵  Sonia Mohan¹  Arkadiusz Gertych⁴ 

[1] Current address: Division of Pathology and Laboratory Medicine, Loma Linda, CA, USA;Department of Biostatistics, Cedars-Sinai Medical Center, Los Angeles, CA, USA;Current address: Surgical Pathology, Super Religare Laboratories and Fortis Hospital, Delhi, India;Departments of Surgery, Cedars Sinai Medical Center, 116N Robertson Blvd. Suite 903, Los Angeles 90048, CA, USA;Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA;Departments of Biomedical Sciences, Cedars Sinai Medical Center, 116N Robertson Blvd. Suite 500, Los Angeles 90048, CA, USA

关键词: Quantification;    Image analysis;    Breast cancer biomarkers;    Tissue decalcification;   

Others  :  1149336
DOI  :  10.1186/s13000-014-0213-9

 received in 2014-07-23, accepted in 2014-10-26,  发布年份 2014

【 摘 要 】

Background

Recent technical advances in digital image capture and analysis greatly improve the measurement of protein expression in tissues. Breast cancer biomarkers provide a unique opportunity to utilize digital image analysis to evaluate sources of variability that are caused by the tissue preparation, in particular the decalcification treatment associated with the analysis of bone metastatic breast cancer, and to develop methods for comparison of digital data and categorical scores rendered by pathologists.

Methods

Tissues were prospectively decalcified for up to 24 hours and stained by immunohistochemistry (IHC) for ER, PR, Ki-67 and p53. HER2 positive breast cancer sections were retrieved from the pathology archives, and annotated with the categorical HER2 expression scores from the pathology reports. Digital images were captured with Leica and Aperio slide scanners. The conversion of the digital to categorical scores was accomplished with a Gaussian mixture model and tested for accuracy by comparison to clinical scores.

Results

We observe significant effects of the decalcification treatment on common breast cancer biomarkers that are used in the clinic. ER, PR and p53 staining intensities decreased 15 ¿ 20%, whereas Ki-67 decreased > 90% during the first 6 hrs of treatment and stabilized thereafter. In comparison with the Aperio images, pixel intensities generated by the Leica system are lower. A novel statistical model for conversion of digital to categorical scores provides a systematic approach for conversion of nuclear and membrane stains and demonstrated a high concordance with clinical scores.

Conclusion

Digital image analysis greatly improves the quantification of protein expression in human tissues. Decalcification affects the accuracy of immunohistochemical staining results and cannot be reversed by image analysis. Measurement data obtained on a continuous scoring scale can be converted to categorical scores for comparison with categorical dataset that are generated by pathologists.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_213 webcite

【 授权许可】

   
2014 Gertych et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

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